1. Field of the Invention
The present application relates generally to the production of semiconductor products and, more particularly, to monitoring production of semiconductor products to detect potential defect excursions.
2. Related Art
In a manufacturing system, such as a semiconductor manufacturing system, products such as chips are manufactured on processing equipment such as a series of manufacturing tools. The products produced occasionally do not sufficiently conform to their specifications and are accordingly considered defective. Ideally, a manufacturing system would prevent defects before they occur, such that the system would not produce a defective product.
Hence, one goal in connection with manufacturing systems for semiconductor wafers is to manage and operate the system to reduce the resulting defects in the products (chips). However, large amounts of defect management and reduction activity are undesirable because such activity takes time and effort, and tends to increase production time and costs, without tangibly contributing to the actual manufacture of the products. At least some defect management and reduction activity is, nevertheless, necessary in order to attain a sufficiently acceptable product.
As a consequence, one major thrust of a defect reduction program is reducing the time that defect management and reduction takes away from manufacturing activity. Taken to an extreme, this focus would result in placing culprit processing equipment offline before it could have any significant negative effect on wafers.
Defective products can result from numerous potential problems, and therefore characterizing the source or sources of a defect can be difficult. One of many possible sources of a defect relates to the health of one or more of the many manufacturing tools on which the product is made. Other sources of problems, include, e.g., variations in raw product, adjustments to recipes, adjustments of specifications, temporary conditions of the tool (e.g., restart) and facility quality.
For some types of defects, such as those relating to stepper and/or etcher tools based on patterned and critical dimension (“CD”) defects, the correlation between source of defect and product yield is relatively straightforward to ascertain. For others, the correlation between source of defect and product yield is not readily determined or available.
Further, at most fabrication facilities, the time from inspection of product to resolution of defect excursions can be several days to several months, depending on the understanding of tracing the root cause of the defect to the tool, and the ability to resolve the original problem with the equipment. Too often the characterization of the defect depends upon obtaining an individual report for the culprit tool, upon the skill of an engineer interpreting the report, and upon word of mouth transferring relevant information about equipment performance between users. With such delays and/or unpredictable exchanges of information, defect excursions tend to be analyzed after the fact, if at all.
Defect management and reduction activity conventionally tends to concentrate in one of two general categories: equipment monitoring and product monitoring. Both involve the inspection of device wafers, but the focus varies from locating defects at the equipment level, or detecting defects created by integrated production.
In the wafer fabrication art, one type of equipment monitoring takes the form of the daily qualification. Daily qualification information (“daily qual”), which can include, e.g., data on particle counts, deposition rate, uniformity, thickness, stress, etch rate, etc. is collected, typically at the start of the day, from numerous manufacturing tools (collectively, “tool health information”). Wafers, such as bare wafers, may be run through a tool for the purpose of obtaining information about tool performance. This information helps characterize the quality of the equipment itself. The tool health information that is collected varies depending on the type of tool and other factors including engineer preference.
Product monitoring information is separately collected relating, e.g., to product wafer measurements and movement from tool-to-tool. Additional information that can be separately collected relates to defect measurements specific to product wafers. This information relates to the quality of the products themselves.
Traditionally, the collected tool health and/or product measurement and movement information is reviewed days or even months after it is generated, if at all. Moreover, the tool health information and product wafer information are not correlated to each other, nor with other information such as from other similar tools (which can be used as a benchmark), other tools in the processing path, nor as a history. Further, such raw information is not conducive to sophisticated analyses such as for predicting trends.
Conventionally, engineers are provided with detailed information on a defect of a product. For example, if an excursion of large flakes is noted on a product wafer, engineers have access to pictures of flakes on the wafer, and a variety of information about the defect on the wafer itself. Unfortunately they have no convenient way of tracking the information about one or more individual wafers in relation to what happened on the tool on the relevant day. Unanswered questions may include: what was the bare wafer daily qualification information for the tool? Are there any hints in the relevant bare wafers at the relevant time(s) that could help solve the problem, such as chamber v. load-lock data which is not available through product wafer measurements?
Thus, there remains a need for a system or method permitting the use of, e.g., tool health information and product wafer information as it is generated, and the correlation of such information. There is also a need for a system that permits the analysis of trends that suggest or predict defect excursions. Further, there is still a need for a defect management methodology that reduces additional processing time needed, in contrast to typical defect measurements.